Weekly Forecasting/Prediction of Energy Data #847
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Hi, I am currently getting my head around this library and trying to figure out if it will suit what I am doing. Basically I am trying to forecast a week of Electricity Consumption data in 30 minute intervals using weather data. I have had some success in building a model to predict_one (The next timestep) of energy data fairly accurately. I want to now evolve this model to always predict a week of data and constantly update with new data received. How does the predict_many & learn_many methods work I haven't been able to find much in the API reference. Will these functions allow me to predict a week of data? Is it possible to predict this far ahead? Is 1 day of data more realistic? Thanks, |
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Replies: 2 comments 3 replies
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That can be tricky, because you need to use weather data estimates, which are themselves predictions. Hope you're aware of it.
I would suggest starting with the HoltWinters method. It should give decent results if your data exhibits some periodicity.
That depends on your data, I can't say without looking at it :) |
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@MaxHalford somewhat related question: has anyone ever started a discussion on the matter "prediction/confidence intervals"? i was going through some suggested sources ( https://otexts.com/fpp2/prediction-intervals.html ) and it seems like some assumption could be made for them, also incrementally. Should i start a new discussion? |
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That can be tricky, because you need to use weather data estimates, which are themselves predictions. Hope you're aware of it.
I would suggest starting with the HoltWinters method. It should give decent results if your data exhibits some periodicity.
That depends on your data, I can't say without looking at it :)